view m-toolbox/classes/@ao/dropduplicates.m @ 49:0bcdf74587d1
database-connection-manager
Cleanup
author
Daniele Nicolodi <nicolodi@science.unitn.it>
date
Wed, 07 Dec 2011 17:24:36 +0100 (2011-12-07)
parents
f0afece42f48
children
line source
+ − % DROPDUPLICATES drops all duplicate samples in time-series AOs.
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ − %
+ − % DROPDUPLICATES drops all duplicate samples in time-series AOs. Duplicates
+ − % are identified by having a two consecutive time stamps
+ − % closer than a set tolerance.
+ − %
+ − % CALL: bs = dropduplicates(as)
+ − %
+ − % INPUTS: as - array of analysis objects
+ − % pl - parameter list (see below)
+ − %
+ − % OUTPUTS: bs - array of analysis objects, one for each input
+ − %
+ − % <a href="matlab:utils.helper.displayMethodInfo('ao', 'dropduplicates')">Parameters Description</a>
+ − %
+ − % VERSION: $Id: dropduplicates.m,v 1.24 2011/04/08 08:56:13 hewitson Exp $
+ − %
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ −
+ − function varargout = dropduplicates(varargin)
+ −
+ − % Check if this is a call for parameters
+ − if utils.helper.isinfocall(varargin{:})
+ − varargout{1} = getInfo(varargin{3});
+ − return
+ − end
+ −
+ − import utils.const.*
+ − utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+ −
+ − % Collect input variable names
+ − in_names = cell(size(varargin));
+ − for ii = 1:nargin,in_names{ii} = inputname(ii);end
+ −
+ − % Collect all AOs
+ − [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+ − [pl, pl_invars] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+ −
+ − % Decide on a deep copy or a modify
+ − bs = copy(as, nargout);
+ −
+ − % Combine plists
+ − pl = parse(pl, getDefaultPlist);
+ −
+ − % Get tolerance
+ − tol = find(pl, 'tol');
+ −
+ − % Get only tsdata AOs
+ − for j=1:numel(bs)
+ − if isa(bs(j).data, 'tsdata')
+ − d = abs(diff(bs(j).data.getX));
+ − idx = find(d<tol);
+ − utils.helper.msg(msg.PROC1, 'found %d duplicate samples', numel(idx));
+ − % Wipe out x samples
+ − if ~isempty(bs(j).data.x)
+ − bs(j).data.x(idx) = [];
+ − end
+ − % Wipe out y samples
+ − bs(j).data.y(idx) = [];
+ − % Wipe out error
+ − if numel(bs(j).data.dx) > 1
+ − bs(j).data.dx(idx) = [];
+ − end
+ − if numel(bs(j).data.dy) > 1
+ − bs(j).data.dy(idx) = [];
+ − end
+ − % set name
+ − bs(j).name = sprintf('dropduplicates(%s)', ao_invars{j});
+ − % Add history
+ − bs(j).addHistory(getInfo('None'), pl, ao_invars(j), bs(j).hist);
+ − else
+ − warning('!!! Skipping AO %s - it''s not a time-series AO.', ao_invars{j});
+ − bs(j) = [];
+ − end
+ − end
+ −
+ − % Set output
+ − if nargout == numel(bs)
+ − % List of outputs
+ − for ii = 1:numel(bs)
+ − varargout{ii} = bs(ii);
+ − end
+ − else
+ − % Single output
+ − varargout{1} = bs;
+ − end
+ − end
+ −
+ − %--------------------------------------------------------------------------
+ − % Get Info Object
+ − %--------------------------------------------------------------------------
+ − function ii = getInfo(varargin)
+ − if nargin == 1 && strcmpi(varargin{1}, 'None')
+ − sets = {};
+ − pl = [];
+ − else
+ − sets = {'Default'};
+ − pl = getDefaultPlist;
+ − end
+ − % Build info object
+ − ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: dropduplicates.m,v 1.24 2011/04/08 08:56:13 hewitson Exp $', sets, pl);
+ − end
+ −
+ − %--------------------------------------------------------------------------
+ − % Get Default Plist
+ − %--------------------------------------------------------------------------
+ −
+ − function plout = getDefaultPlist()
+ − persistent pl;
+ − if exist('pl', 'var')==0 || isempty(pl)
+ − pl = buildplist();
+ − end
+ − plout = pl;
+ − end
+ −
+ − function pl = buildplist()
+ − pl = plist();
+ −
+ − % tol
+ − p = param({'tol','The time interval tolerance to consider two consecutive samples as duplicates.'}, ...
+ − {1, {5e-3}, paramValue.OPTIONAL});
+ − pl.append(p);
+ −
+ − end
+ −
+ −